Triple
T33093515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Slinky |
E846845
|
entity |
| Predicate | hasJingleLyric |
P18290
|
FINISHED |
| Object | "It's Slinky, it's Slinky, for fun it's a wonderful toy" |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: "It's Slinky, it's Slinky, for fun it's a wonderful toy" | Statement: [Slinky, hasJingleLyric, "It's Slinky, it's Slinky, for fun it's a wonderful toy"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasJingleLyric Context triple: [Slinky, hasJingleLyric, "It's Slinky, it's Slinky, for fun it's a wonderful toy"]
-
A.
hasLyric
chosen
Indicates that one entity (typically a musical work or track) contains or is associated with the lyrics provided by another entity.
-
B.
hasLyricsIn
Indicates that the lyrics of a work are written or available in a specified language.
-
C.
hasLyricsFeature
Indicates that something possesses a particular characteristic or attribute related to its lyrics.
-
D.
hasLyricsTone
Indicates the tonal quality or emotional character expressed by the lyrics of a piece of music.
-
E.
hasLyricalLanguage
Indicates that something (such as a text or expression) employs poetic, expressive, or highly figurative language.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f3495590dc8190aa04f3dec74ce976 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d6a6b04c8190bee4cf9c00665ef7 |
completed | May 3, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69f6d27120988190aacec621cf2bf0e8 |
completed | May 3, 2026, 4:43 a.m. |
Created at: May 1, 2026, 1:26 a.m.